Triple
T14746266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Surgut International Airport |
E346476
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Surgut |
E490651
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Surgut | Statement: [Surgut International Airport, serves, Surgut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Surgut Context triple: [Surgut International Airport, serves, Surgut]
-
A.
Surgut
chosen
Surgut is a major oil-producing city in western Siberia, Russia, known as an important industrial and transportation hub in the Khanty-Mansi Autonomous Okrug.
-
B.
Omsk
Omsk is one of the largest cities in southwestern Siberia, Russia, serving as a major industrial, cultural, and transportation hub on the Irtysh River.
-
C.
Barnaul
Barnaul is a significant industrial and cultural city in southwestern Siberia, Russia, located near the Ob River and serving as a key regional center.
-
D.
Ust-Kamenogorsk
Ust-Kamenogorsk is an industrial city in northeastern Kazakhstan, known as a major center for metallurgy and winter sports.
-
E.
Nizhnevartovsk
Nizhnevartovsk is a major oil-producing city in western Siberia, Russia, known as one of the centers of the country’s petroleum industry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d002708190a32a4a45e96fc389 |
completed | April 14, 2026, 11:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b43360481908dc73d5e6758fea6 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 1:30 a.m.